In
recent years the observation that "irreversible processes converge to
equilibrium faster than their reversible counterparts" has sparked a
significant amount of research to exploit irreversibility within sampling
schemes, thereby accelerating convergence of the resulting Markov Chains. It is
now understood how to design irreversible continuous-time dynamics with
prescribed invariant measure. However, for sampling/simulation purposes, such
dynamics still need to undergo discretization and, as it is well known, naive
discretizations can completely destroy all the good properties of the
continuous-time process.
In
this talk we will i) give some background on irreversibility ii) present some pros and cons of using
irreversible proposals within reversible schemes (Joint work with K.
Spiliopoulos and N. Pillai).

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